RiskEdge

Learn how to maximize profits while mitigating risks, acting as a broker.

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Inspiration

As someone new to stock investing, I was immediately fascinated by the market and the endless opportunities it presents. The thrill of making trades, analyzing trends, and seeing my portfolio move was exhilarating. However, reality hit hard—I quickly found myself down $200, realizing that I lacked a proper understanding of risk management and portfolio diversification.

I didn’t just want to accept the losses—I wanted to learn from them and build something that could help others avoid the same mistakes. That's where RiskEdge was born—an AI-powered Game that helps investors understand, manage, and mitigate risk, ensuring smarter and more informed financial decisions.

What it does

RiskEdge is an AI-powered platform that helps users manage investment risk by:

Generating a personalized investor profile based on the user's preferences and risk tolerance. Allowing users to select stocks and visualize their portfolio allocation. Providing real-time stock prices and an updated remaining balance. Analyzing portfolio risk using machine learning models, including Sharpe ratios, Value-at-Risk (VaR), and volatility clustering. Offering insights and suggestions for optimizing portfolio allocation to balance returns and risks effectively.

How we built it

Frontend: Developed using React, Next.js, and Tailwind CSS, with Framer Motion for smooth animations Backend: Built with FastAPI, handling API requests for risk analysis and portfolio generation. Data Processing: Used Yahoo Finance API to fetch real-time stock prices and historical data for risk calculations. Machine Learning: Implemented K-Means clustering and risk assessment models in Python (NumPy, Pandas, scikit-learn) to categorize stocks based on volatility and risk levels. Deployment: Integrated GitHub for deployment.

Challenges we ran into

Handling real-time stock price updates without excessive API calls. Ensuring accurate risk assessment models that effectively categorize stocks into risk levels. Frontend-backend communication issues, particularly in maintaining API efficiency while fetching stock data. Designing a modern UI that is both intuitive and visually appealing while keeping load times low.

Accomplishments that we're proud of

Successfully integrated AI-powered risk analysis for stock portfolios. Developed a visually stunning UI that aligns with modern fintech applications. Overcame technical hurdles with API optimizations, caching, and performance tuning. Created an engaging and interactive portfolio selection experience that dynamically updates risk insights in real time.

What we learned

Optimizing API calls is crucial for handling real-time stock data efficiently. Machine learning models can significantly improve financial decision-making by identifying risk patterns. User experience (UX) and UI design play a major role in making complex data digestible and interactive. Balancing performance and functionality in a real-time financial application is a rewarding challenge.

What's next for RiskEdge

Options & ETFs support: Expand stock selection to include options trading and ETFs. Advanced risk modeling: Implement Monte Carlo simulations for even better portfolio optimization. Predictive AI models: Use deep learning to forecast market trends and help investors make smarter decisions. Mobile app development: Build a mobile-friendly version for easier access. Community & social investing: Allow users to compare portfolios, see trending stocks, and learn from top investors.

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